Inside Twitter: Data Analysis for Journalists

Jour 405v, Jour 5003, Spring 2019

Rob Wells, Ph.D.

University of Arkansas

School of Journalism and Strategic Media

rswells@uark.edu

@rwells1961

Course Goal: Students will learn the latest data journalism techniques that drive modern newsrooms and public relations / advertising offices. The class will extract and analyze Twitter data with the goal of producing an interactive multimedia presentation.

Course Description: This course will teach students how to code in programs such as R and SQL and how these powerful tools are used in modern news reporting. Quality reporting in newsrooms requires a solid foundation of data analysis. The data skills taught in this class are in high demand in newsrooms and corporations.

Required Text: Machlis, Sharon. Practical R for Mass Communications and Journalism. Chapman & Hall/CRC The R Series. 2018. ISBN 9781138726918 https://www.amazon.com/gp/search?keywords=9781138726918

Link to several free chapters: “CNTL” + click for a New Tab

Syllabus - Jour 405v:: “CNTL” + click for a New Tab

Syllabus - Jour 5003: “CNTL” + click for a New Tab

Course Website: “CNTL” + click for a New Tab

Upon completion of this course, you will celebrate like this:


Week #1:Introduction and R Basics

Agenda: –1/14/2019 - Week 1

–Email to students

–Discuss syllabus

–Intro R and R Studio. Open program.

Machlis website:
http://www.machlis.com/R4Journalists/index.html

–R interface explained: Four main windows

  Script writing, R Markdown, Table Viewer: Upper Left  
  Environment - data loaded in R: Upper Right  
  Console - write commands in R: Lower Left  
  File Manager and Html table viewer: Bottom Right
  

https://docs.google.com/presentation/d/1O0eFLypJLP-PAC63Ghq2QURAnhFo6Dxc7nGt4y_l90s/edit#slide=id.g1bc441664e_0_10

–Show basic R skills.

–Loading software. Tidyverse
Rio

–Conventions in coding.

–How many rows? nrow(yourdataset)

–How many columns? ncol(yourdataset)

–What is in the first five rows? head(yourdataset)

–rename columns. create columns

##Wednesday, Jan. 16
–Misc
Class intros Book - Amazon Installation issues on laptops? Twitter feeds: @rstudiotips
–Run demos from Ch. 3
–Show Collins results
–Twitter analysis of Trump Tweets http://varianceexplained.org/r/trump-tweets/
–Ch 1 & 2 of Machlis: Key Points
Reproducible research Repetitive tasks in modern newsrooms. Employment reports, crime stats, budgets Variables - an R object Assignment operator <- Case sensitive Vector: A vector can only have one type of data - all integers, all strings Dataframe - like a spreadsheet Save files - Don’t save workspace: because all of your variables will be stored and re-loaded the next time you launch RStudio. It’s too easy to forget about previously stored variables that can interfere with later work,
–Software packages: tidyverse, rio, pacman
–Software: How to get details and help
help(package=“dplyr”) browseVignettes(“NameOfPackage”) help(“NameOfFunction”) ??median
–Data Types and R
Machlis: 2.4.2 Data types you’re likely to use often
–EXERCISES: Excel vs R –Load tutorial: Introduction-to-R-January-2019.R > Download this file and open it in R Studio
–Left click on the page, remove .txt extension, save as all files
–Keyboard Shortcuts
Tab - Autocomplete Control (or Command) + UP arrow - last lines run Control (or Command) + Enter - Runs current or selected lines of code in the top left box of RStudio Shift + Control (or Command) +P - Reruns previous region code
**Notes:** –Basic descriptive statistics —Review ComputerWorld’s Beginner’s Guide To R –Stack Overflow at stackoverflow.com
Reading:
–Machlis. Chapter 1 & 2.
–Beginner’s guide to R: https://www.computerworld.com/article/2497143/business-intelligence/business-intelligence-beginner-s-guide-to-r-introduction.html
–Twitter analysis of Trump Tweets http://varianceexplained.org/r/trump-tweets/
–Review another R tutorial https://docs.google.com/presentation/d/1zICxR7qDM3RQ2Nxi5CqHlM3H8I7qoVkNtqcNcnbbDCw/edit#slide=id.p
Resources: RStudio Navigation Tricks You Might’ve Missed https://rviews.rstudio.com/2016/11/11/easy-tricks-you-mightve-missed/
How Do I? https://smach.github.io/R4JournalismBook/HowDoI.html
Functions https://smach.github.io/R4JournalismBook/functions.html
Packages https://smach.github.io/R4JournalismBook/packages.html

Week #2: File management

Agenda: –1/21/2019 - Week 2

Wednesday, Jan. 23

–Next week Quiz on Basic R functions described so far in exercises.

–Readings / Coursework for MA Students > Sign up for this free class from Nick Diakopolous

--Workload TBD - I will assign select videos and readings from this class. 

Exercise

–Load tutorial: Introduction-to-R-January-2019.R > Download this file and open it in R Studio

–Based on this tutorial, perform this exercise:

1. Percentage change from 2010-2017.
2. Produce a table with 5 counties with most growth. 
3. Produce table with 5 counties with greatest population loss
4. Graph the top 5 and bottom 5
5. Filter just Benton County’s population for 2015
6. And if you finish that, bring up AOC.csv. How many rows? How many columns?
7. AOC.csv filter the text field for “Pelosi” or “Trump” or “New Deal"

The course GitHub Page > Here it is

–See Data folder

Click AOC.csv   
"View raw"   
Cntl + click (or right click) - Save As - AOC.csv   

Ch 3 & 4 of Machlis: Key Points

Ch 3 Exercises:
Stock chart exercise used quantmod is a library for financial analysis. 
dygraphs creates *interactive Web graphics* of data over time.
Median Income for a City
Loading packages

Ch 4 Importing Data
How read.table() works for importing data:      
Loading data
Manipulating data: dplyr -  stringr
Data Management: mutate rename bind_rows 

Exercise

–Loading Data from U.S. Census & Student Loans –Load tutorial: Downloading Data 12-24-18.R > Download this file and open it in R Studio

–Loading and basic file management

Bringing in data
Data Frames
Extracting interesting details
Cleaning the data
Reshaping the format
Manipulating the data
Exporting  
Add a column with a math conversion  

–Math –Summary Statistics

summary(Crime)

mean(x) Calculate the mean, or average, for variable x. median(x) Calculate the median. max(x) Find the maximum value. min(x) Find the minimum value. sum(x) Add all the values together. n() Count the number of records. Here there isn’t a variable in the brackets of the function, because the number of records applies to all variables. n_distinct(x) Count the number of unique values in variable x.

–Using a function for an equation
percent_change <- function(first_number, second_number) { pc <- (second_number-first_number)/first_number*100 return(pc) }

percent_change(100,150) [1] 50

This is what’s happening in the code above: * percent_change is the name of the function, and assigned to it is the function function() * Two variables are necessary to be passed to this function, first_number and second_number * A new object pc is created using some math calculating percent change from the two variables passed to it * the function return() assigns the result of the math to percent_change from the first line Build enough functions and you can save them as your own package.

–Set up column for math calculations Example: Total column shows winter snowfall in inches. To add a column showing totals in Meters, you can use this format:
.snowdata\(Meters <- snowdata\)Total * 0.0254

–Export data Write Export output this file to a CSV or Excel write.csv or write.excel write.csv(AR2016_SMALL,“AR2016_SMALL.csv”)

Reading:

–Machlis. Chapter 3 & 4.

–Study Twitter meta data
https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/tweet-object.html

–Look at this example: Ocasio.csv (in data folder of course page)

–Cohen, “Numbers in the Newsroom,” Common Mistakes.

–String data manipulation https://dereksonderegger.github.io/570L/13-string-manipulation.html

–Follow StoryBench, Northeastern Univ. https://twitter.com/storybench

Resources
–Use R instead of Excel: Andrew Ba Tran
Excellent Tutorial Spelling out Excel and Comparable Commands in R
https://trendct.org/2015/06/12/r-for-beginners-how-to-transition-from-excel-to-r/
Basic data work- head to http://bit.ly/excel_and_r

–All Cheat Sheets https://www.rstudio.com/resources/cheatsheets/


Week #3: R Twitter Data. Data Types. Scripts

Agenda –1/28/2019 - Week 3

Monday, Jan. 28

Quiz on Basic R functions for Wednesday

–Describe Assignment #1 due Feb. 6: Managing Data / Static Graphic

–Key Concepts - Tasks This Week:

Dplyr: Filters, Grouping, Sorting, pipes %>%  
Basic data visualization  
Tidyverse 
Work with sample Twitter data

Exercises

Basic Data Visualization 12-26-18.R
Median Income For City.R Work with sample Twitter data

Notes

–DPLYR Five basic verbs • filter() • select() • arrange() • mutate() • summarize() plus group_by()

–Pipes - a Much-Used Command to Link Filters, Functions

pipe %>%
CMD +  Shift + M   

–Presentation from Bob Rudis on Writing Readable Code with Pipes, delivered at the rstudio::conf 2017. https://www.rstudio.com/resources/videos/writing-readable-code-with-pipes/ Pipes as a way of chaining commands. object %>% operation() —> result

–Visualizing data

ggplot2 - charts and maps
htmlwidgets - web visualization interactives
plotly - exporting charts online
Chart
Export Static chart 

–Data Wrangling-Text Mining in Twitter.

See entire scraping sequence. Extract from Twitter.

Reading Machlis Chs. 5 & 6.

Seth C. Lewis, et al. “Big Data and Journalism: Epistemology, Expertise, Economics and Ethics,” Digital Journalism, 2015

Transforming and Analyzing Data dplyr.pdf – Andrew Ba Tran, Washington Post

For working with dates library(lubridate) Dealing-with-dates.pdf by Andrew Ba Tran

–Read Kavanaugh text mining story: Text analysis of Brett Kavanaugh’s opinion.
http://www.storybench.org/bringing-textual-analysis-tools-to-judge-brett-kavanaughs-latest-opinion/

Resources:

–For analysis library(dplyr)

Wednesday, Jan. 30

Quiz on Basic R functions

–Setting up an R Workflow –Twitter Metadata
–Work with sample Twitter data –Lubridate

Exercises

Basic crime rate in R exercise.txt Basic-Chart-January-2018.R
Twitter Metadata
Work with sample Twitter data


Week #4: Using R to build basic graphs and charts

Agenda –2/4/2019 - Week 4

Assignment #1 due Feb. 6: Managing Data / Static Graphic

–GGplot
–Conventions in coding
–R Markdown
–Work with sample Twitter data

Exercises –Ch. 3.8 Run a remote script to make an interactive map

Notes

–A handy explanation of ggplot and its components
If you’re using ggplot: plus it! For everything else: pipe it!

So geom_point() geom_bar() geom_boxplot()

Notes

–Setting up an R Workflow http://learn.r-journalism.com/en/publishing/workflow/r-projects/

Resources
Basic Charts in R
https://www.youtube.com/watch?v=1EUJ0tsVsUA&t=12s

GGplot Video from Andrew Ba Tran
https://www.youtube.com/watch?v=Sx7d7eGRSj0&t=9s

Reading
Machlis Chs. 7 & 8.
Samantha Sunne, “The Challenges and Possible Pitfalls of Data Journalism, and How You Can Avoid Them,” American Press Institute, 2016

charts_with_ggplot by Andrew Ba Tran, Washington Post


Week #5: Using R to build basic graphs and charts

Agenda –2/11/2019 - Week 5

–Themes for data viz library(ggthemes)

—-Work with sample Twitter data

–Terminology

ggplot
aes

**Resources*
Grammar of Graphics http://vita.had.co.nz/papers/layered-grammar.html

–Graphing GGplot 12-28.R Exercises from Machlis Ch. 9. Facets

Notes –The pie chart focuses the reader on large percentages, and encourages the reader to think of the total –The stacked bar plot provides the same information, but makes it easier to accurately determine at a glance how large each group is out of the whole. –This bar chart splits the categories horizontally, and draws attention to how the family members are ordered. It encourages the reader to think about the distribution rather than disconnected categories, and gives a better sense of sense of scale.

Reading:
Machlis Chs. 9 & 10
Albert Cairo, “The Functional Art,” Principles of Data Visualization.

Exercises
–Create R Markdown document, export to PDF, HTML
–Class Exercise - Graphing and Grouping Data Viz Exercise 2 From Ch 9


Week #6: GitHub

Agenda –2/18/2019 - Week 6

–Create a GitHub account. https://github.com/

–Follow this tutorial https://guides.github.com/activities/hello-world/

This class is intended to teach you modern workflow techniques for coding. A centerpiece of that workflow is GitHub. This is a website with a system that allows you to collaborate with other programmers on coding projects. It manages versions of software code and is a very popular with the tech elite.

Your GitHub account, which is public, represents an important professional image. Prospective employers and collaborators will look at your GitHub account.

–Andrew Ba Tran Tutorials on GitHub Git and Github Pages http://learn.r-journalism.com/en/git/

Installing Git https://journalismcourses.org/courses/RC0818/installing_git.pdf

GIT https://journalismcourses.org/courses/RC0818/git.pdf

Connecting to Github https://journalismcourses.org/courses/RC0818/github.pdf http://learn.r-journalism.com/en/git/github/github/

Best Practices for Github http://learn.r-journalism.com/en/git/github_pages/github-pages/

–Loading and basic file management

Commit  
Branch  
Pull Request  
Fork  

Resources on GitHub

–GitHub flow
https://guides.github.com/introduction/flow/

–GitHub Guides
https://guides.github.com/

–Another GitHub guide
https://andrewbtran.github.io/NICAR/2018/workflow/docs/03-integrating_github.html

Reading:
Machlis Chs. 11 & 12

Installing Git for a Mac - Andrew Ba Tran

Exercises

Pair up.  
Team 1 takes this code. Make changes.    
Team 2 forks the code. Makes changes.  
Pull & Commit  

Workbooks, Markdown


Week #7: Twitter

Agenda –2/25/2019 - Week 7

Due Feb 27: Assignment #2. Visualization of Twitter data

–Analyzing Tweets from public officials. Dataset TK

–Study Twitter meta data
https://twittercommunity.com/ https://developer.twitter.com/en/docs

–Register as Twitter Developer https://developer.twitter.com/en/account/get-started

Reading Machlis Chs. 13 & 14.
Twitter meta data

Resources:

Exercises


Week #8: R Markdown

Agenda –3/4/2019 - Week 8

Quiz on GitHub

–R Markdown, Desktop Publishing –Andrew Ba Tran - Week 5 Publishing http://learn.r-journalism.com/en/publishing/ –R Markdown http://learn.r-journalism.com/en/publishing/rmarkdown/rmarkdown/ –More R Markdown http://learn.r-journalism.com/en/publishing/more_rmarkdown/more-rmarkdown/

–Rendering html as an output in GitHub
https://rmarkdown.rstudio.com/lesson-9.html https://github.com/rstudio/cheatsheets/raw/master/rmarkdown-2.0.pdf

–R Markdown Formatting
Sizing images: <.img src=“drawing.jpg” alt=“drawing” width=“200”/>
(Note: Remove the period before “img”) https://rpubs.com/RatherBit/90926

–Terminology

Render  
Html  
Markdown  

Notes R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

Including Plots

You can also embed plots, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

Reading
Machlis Chs. 15 & 16

Resources:

Exercises

Line breaks: Use HTML tags. Adding
will give a single line break – option for when two-space indentation is ignored.


Week #9: Text Mining

Agenda –3/11/2019 - Week 9

Extra Grad Assignment - Scraping Twitter. Due March 13.

–Basic text mining techniques
–Lubridate

Reading Machlis Chs. 17 & 18

Resources:

–Joining Dataframes in R
https://www.youtube.com/watch?v=gLg4D9bMIyc&t=13s

–Data Wrangling http://learn.r-journalism.com/en/wrangling/

http://learn.r-journalism.com/en/wrangling/dplyr/dplyr/

https://github.com/r-journalism/learn-chapter-3/blob/master/dplyr/pipes-dplyr.R

Exercises Data Wrangling-Text Mining in Twitter.R


SPRING BREAK – March 18-22 – MAKE GOOD LIFE CHOICES

.


Week #10: Mapping in R

You will make this in the class

Agenda –3/25/2019 - Week 10

Due March 27: Assignment #3. Interactive Map

–Produce a basic interactive map in R, post on WordPress

–Andrew Ba Tran - Week 4 Mapping http://learn.r-journalism.com/en/mapping/

Reading “Connecting the Dots” by Jacob Harris (2015) and discuss how people should or should not be represented through news visualizations.

What is code? http://www.bloomberg.com/graphics/2015-paul-ford-what-is-code/

Resources: –Visual Narrative Tricks by Albert Cairo https://www.youtube.com/watch?v=TSGaueL4Ggk

Spatial data maptools - work with shapefiles

Exercises –Maps in R 12-28-18.R


Week #11: Mapping in R

Agenda –4/1/2019 - Week 11
–Produce a basic interactive map in R, post on WordPress

–You will make this in the class

Reading Bad data visualizations. Data Translation.

The Journalist as Programmer: A Case Study of The New York Times Interactive News Technology Department http://isoj.org/wp-content/uploads/2016/10/ISOJ_Journal_V2_N1_2012_Spring.pdf

Resources:

Exercises –Maps Spatial Analysis Tutorial.R


Week #12: Web Scraping in R

Agenda –4/8/2019 - Week 12

–Web Scraping in R
–Application Programming Interface - API
Twitter historical API https://developer.twitter.com/en/docs/tutorials/choosing-historical-api

–See 4.8 in Machlis: ‘Scrape’ data from Web pages with the rvest package and SelectorGadget browser extension or JavaScript bookmarklet. SelectorGadget helps you discover the CSS elements of data you want to copy that are on an HTML page; then rvest uses R to find and save that data. This is not a technique for raw beginners, but once you’ve got some R experience under your belt, you may want to come back and re-visit this. I have some instructions and a video on how to do this at http://bit.ly/Rscraping. RStudio has a webinar available on demand as well, at https://www.rstudio.com/resources/webinars/extracting-data-from-the-web-part-2/ .

Reading Julia Angwin, Terry Parris Jr., Surya Mattu. “Breaking the Black Box: What Facebook Knows About You,” ProPublica, 2016;

Nicholas Diakopolous, “Algorithmic Accountability,” Digital Journalism, 2014.

APIs - basics https://medium.com/@LewisMenelaws/a-beginners-guide-to-web-apis-and-how-they-will-help-you-23923a0da450

A gentle introduction to APIs for data journalists https://trendct.org/2016/12/29/fetching-airport-delays-with-python-a-gentle-guide-to-apis-for-journalists/

MA Students –Sign up for a Census API key: https://api.census.gov/data/key_signup.html

Resources:

Exercises –MA Students, Census API exercise


Week #13: Web Scraping in R

Agenda –4/15/2019 - Week 13
– Web Scraping in R

Reading –Twitter analysis of Trump Tweets http://varianceexplained.org/r/trump-tweets/

Different types of Twitter APIs https://developer.twitter.com/en/products/products-overview

Amy Webb future of journalism trends https://futuretodayinstitute.wetransfer.com/downloads/0e84e883e140bafe9a3436a6464032be20171003123607/ecda17 Resources:

Exercises Continue with Week 12 materials


Week #14: Sentiment Analysis - Final Project

Agenda –4/22/2019 - Week 14

–Sentiment Analysis

Reading –Sentiment analysis http://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm

–Saif Mohammad research on sentiment analysis
http://saifmohammad.com/index.html

Resources:

Exercises

Collins sentiment analysis 10-13-18.R


Week #15: Wrap Up

Agenda –4/29/2019 - Week 15

Assignment #4 Final Project: Interactive Data Visualization


RESOURCES

Download R and RStudio

This program is loaded on all of the computers in Kimpel 146. You can load it on your laptop as well. It is not large and doesn’t tax the memory a lot. R runs on Windows, Mac and Linux, but this course uses the Mac version. If you use Windows on your personal laptop, the instructor is not responsible for any variations in the lessons and instructions.

First, download the most recent version of R at https://www.r-project.org/, . Look for the link to download R. Click that download option and you should be taken to CRAN, the Comprehensive R Archive Network, and a list of CRAN servers, called mirrors, around the world. Pick a server and choose the precompiled binary distribution for your operating system. Once the file finishes downloading, install it like any other software program – run the .exe for Windows or .pkg for Mac.

Accept all of the default settings for Mac.

Second, install RStudio, an excellent user interface that helps you manage and create R code. Download the open source edition of R Studio desktop and follow the prompts to install it. http://www.rstudio.com/products/rstudio/download/

More information: http://www.machlis.com/R4Journalists/download-r-and-rstudio.html